Sentra vs Coworker: Company Brain vs AI Coworker

TL;DR

• Coworker.ai is a personal AI app from Coworker LLC that bundles ChatGPT, Claude, and Gemini behind one interface for individuals and small teams on Apple devices.
• Sentra is a company brain. One org-wide memory graph that humans and every agent read and write through REST or MCP.
• The core split is scope. Coworker.ai gives one person a versatile assistant, while Sentra gives the whole company a shared memory with commitment tracking and contradiction detection.
• Choose Coworker.ai if you want one subscription for multiple frontier models, document drafting, translation, and image generation.
• Choose Sentra if your people and agents need a single source of truth that never restates stale facts as current.

What Is Coworker.ai? (A Quick Disambiguation)

Three products carry the "coworker" name, and only one is in this comparison. The site coworker.com runs a coworking-space marketplace with no connection to AI. The nonprofit at coworker.org advocates for workers and labor organizing, also unrelated.

The product reviewed here is Coworker.ai, made by Coworker LLC and sold through the App Store as a native app for iOS, iPadOS, macOS, and visionOS. It bundles frontier models behind one interface, so a single person reaches OpenAI's ChatGPT, Anthropic's Claude, and Google Gemini without juggling separate apps or subscriptions. Beyond model access, it drafts emails and articles, generates images from text, translates across 100+ languages, and summarizes documents, then syncs that work across a person's Apple devices.

The developer aims it at professionals, students, content creators, and entrepreneurs who want AI help on their own machines. Coworker.ai builds for the individual. Nothing in its listing mentions shared team knowledge, multi-user workspaces, or memory that persists across an organization.

What Is Sentra?

Sentra is a company brain. It builds one queryable graph that every human and every agent in your organization reads and writes. What you teach one agent, every agent remembers. That shared graph is the structural difference from a personal assistant, where each session starts fresh and nothing carries across people or tools.

Sentra captures meetings, messages, docs, tickets, code, and CRM data across 200+ integrations, then extracts entities, relationships, and decisions automatically. There is no tagging or filing to maintain. The memory organizes itself into three layers: what is true and where it came from, what people promised and what is blocked, and who said what and what they meant.

Three mechanisms set Sentra apart, each covered below. Its bi-temporal graph stamps every fact with when it became true and when it stopped, so agents never restate deprecated information as current. Write-time comprehension resolves meaning at ingestion rather than guessing at query time. Commitment tracking captures promises the moment they are spoken and flags contradictions before they reach a customer.

How This Comparison Was Evaluated

These two products solve different problems for different buyers, so we judged each against the job it actually does rather than forcing a single scorecard. We scored both on five dimensions: memory model, collaboration scope, agent support, deployment and compliance, and personal productivity. Coworker.ai wins on the last one, since it gives one person fast access to several frontier models. Sentra owns the first three, because it stores and shares context across an entire organization. They appear in the same conversation because both attach the word "AI" to daily work, but one is a personal assistant and the other is shared memory. The comparison exists to help you pick the right one.

Snapshot Comparison

Model Access and Personal Productivity

Coworker.ai wins the personal productivity dimension outright, because it puts three frontier models behind one interface a single person controls. You open the app and switch between OpenAI ChatGPT, Anthropic Claude, and Google Gemini without managing three separate accounts or subscriptions. The app adds text-to-image generation in multiple styles, translation across 100+ languages with idiom preservation, and document summarization, all synced across your iPhone, iPad, and Mac. A 30-day free trial with full premium access and no credit card lets you test the whole thing before paying. For a writer, student, or solo founder who wants to draft, translate, and generate images from one place, that breadth is the entire value.

Sentra does none of this, and it isn't trying to. Sentra is not a chat app you open and talk to. It pairs with the models you already use rather than replacing them, sitting underneath as the memory layer your agents read from and write to over REST or MCP. If your team runs Claude in one tool and ChatGPT in another, Sentra gives both the same shared context instead of giving you a fourth interface to switch into.

That difference reflects the buyer each product names. Coworker LLC built a versatile assistant for one person across Apple devices. Sentra built a company brain for an organization where many people and many agents need the same facts. Asking which has better model access misreads the categories. Coworker.ai aggregates models for personal output. Sentra remembers what your existing models and people produce, so nothing a colleague taught one agent gets lost when another agent picks up the work.

Shared Organizational Memory

Coworker.ai keeps no shared memory across people. Each session belongs to one user on one device, and the app syncs that user's own conversations across their Apple devices through cross-device sync. Nothing one person learns inside Coworker.ai becomes available to a colleague, because the App Store listing describes no team-wide knowledge base, no multi-user workspace, and no organizational store of any kind. Two coworkers using it ask their questions in isolation, and neither benefits from what the other already discovered.

Sentra replaces that isolation with one graph that every human and every agent reads and writes. The graph holds three coordinated layers. Factual memory records what is true, where it came from, and when it changed. Action memory records what someone promised, what is blocked, and what needs follow-up. Interaction memory records who said what, what they meant, and which perspective shaped a decision. Access runs through REST or MCP, so a sales rep, a support engineer, and a Cursor coding agent all touch the same store rather than separate per-session caches.

The mechanism produces a property no single-user assistant can match. What you teach one agent, every agent remembers. When a Claude agent records a customer's contract exception in Sentra, a later GitHub or Linear agent reads that same fact without anyone re-entering it, because both wrote to and read from one organizational graph. Sentra builds this store automatically by syncing meetings, messages, docs, tickets, code, and CRM data, then extracting entities, relationships, and decisions without manual tagging or filing.

That difference decides which buyer each tool fits. Coworker.ai serves the individual who wants a capable assistant on their own laptop and phone. Sentra serves the organization where many people and agents must trust the same context, and where knowledge held by one person or session has to reach everyone else. The first is a personal tool. The second is shared memory the whole company depends on.

Bi-Temporal Memory and Staleness Prevention

A model answers from whatever it learned in training plus whatever sits in the current chat. Coworker.ai works this way. It bundles ChatGPT, Claude, and Gemini behind one interface, and each of those models responds from training data and the active session. Nothing in the App Store listing describes a persistent memory that carries facts forward, which means a fact you correct on Monday is gone by Tuesday's fresh conversation.

That design produces a specific failure once facts change. Picture your standard payment terms moving from net-60 to net-30 in March. A retrieval system that stores both versions side by side treats them as equally valid, so an agent drafting a contract in June can pull the old net-60 clause and present it as current. Vector search returns what is close to the query, not what is true right now.

Sentra solves this by giving every fact two timestamps. The first marks when the fact became true. The second marks when it stopped being true. When net-30 replaces net-60, Sentra does not delete the old term. It invalidates it by stamping the moment it expired, then records net-30 as the active fact. Old facts stay in the graph as history, but no agent reads them as the present.

The practical effect is that any model querying Sentra gets the version that holds today, with the superseded version clearly marked as past. An agent writing your June contract sees net-30 and the date net-60 ended. Coworker.ai has no equivalent because it has no shared store of facts to version in the first place. It restates whatever the model happens to recall.

Commitment Tracking and Contradiction Detection

Sentra tracks what people promise from the moment they say it, and Coworker.ai has no equivalent. A sales rep grants a verbal 60-day MSA exception on a call and never writes it down. Sentra captures that commitment at ingestion, attaches the recording or transcript as evidence, and flags it when the contract ships without the exception. The promise stops living only in one person's memory.

The mechanism is proactive monitoring against the action layer of Sentra's graph. Sentra logs who promised what, what is blocked, and what needs follow-up, then surfaces slippage before anyone thinks to ask. In one tracked example across four design partners, Sentra followed six commitments and reported the outcome of each. Four shipped, one slipped, and one was dropped entirely. No one had to assemble that status by hand.

Coworker.ai works the other way. It answers the question you type into it, then waits for the next one. The app holds no shared org memory, so it cannot notice that a promise made in March went unmet in May, because it never recorded the promise and never sees the rest of your organization's activity. A frontier model behind a single interface responds to prompts. It does not watch for drift.

That gap matters most when commitments cross people and weeks. A personal assistant helps you draft the follow-up email once you remember to send it. Sentra is the layer that reminds you the follow-up is overdue, names the deprecated promise, and shows the evidence behind it.

Agent Integration

Coworker.ai is the agent. You open the app, type a prompt, and a frontier model answers. The product is the conversation itself, and it ends when you close the session. Nothing the model learns in one chat carries into the next person's work, because there is no shared layer underneath to write it to.

Sentra is the memory the agents read from and write to. It exposes a REST API and an MCP endpoint, so any agent you already run connects to the same org graph. Claude, Cursor, Codex, Windsurf, and Perplexity all read and write to one source of truth instead of carrying isolated per-session context.

That difference compounds. When a Cursor session resolves how a service handles retries, Sentra captures the decision at write time, and the next agent that touches that code reads it without anyone re-explaining. What you teach one agent, every agent remembers. Coworker.ai cannot do this, because each session starts from training data and the current prompt with no persistent org context behind it.

The framing matters for your stack. Sentra is memory for your agents, not a replacement for them. You keep Cursor for code and Claude for reasoning, and Sentra sits underneath as the shared context all of them draw on. Coworker.ai asks you to work inside its single app. Sentra works wherever your agents already run through the 200+ integrations and MCP it ships with.

Deployment, Compliance, and Enterprise Readiness

Coworker.ai is a consumer app, and its data practices reflect that. It runs only on Apple devices, with builds for iOS 15.1+, iPadOS, and macOS 12.0+ on M1 or later, and the macOS version is listed as not verified for that platform. The App Store listing shows the app collects coarse location, physical address, email, name, and phone number, all linked to user identity (App Store). Support runs through email at support@coworker.im, and the listing names no SOC 2, ISO, or other compliance certification. A solo professional can accept that tradeoff. A security team reviewing a vendor cannot.

Sentra is built for the second reader. You can run it in the cloud, inside an isolated VPC, or fully air-gapped on-prem when the data cannot leave your network. Sentra holds SOC 2 Type II and ISO 27001 certifications, and it does not train models on customer data. Its subprocessors are named directly, including AWS, Google Cloud Platform, Slack, GitHub, and OpenAI.

The gap follows from what each product is. Coworker.ai serves one person who downloads an app and agrees to its terms. Sentra serves an organization whose procurement, legal, and security functions sign off before a single document syncs, so deployment isolation and audited certifications are the entry requirement, not an upgrade.

Best For: Coworker.ai

Coworker.ai fits one person who wants several frontier models behind a single subscription. Instead of paying for and switching between ChatGPT, Claude, and Gemini separately, you open one app and pick the model that suits the task. Writers, students, content creators, and solo entrepreneurs get the most from it, since their work centers on drafting documents, generating images, and translating across 100+ languages.

The 30-day free trial with no credit card lowers the barrier to testing it, and cross-device sync keeps your conversations consistent across iPhone, iPad, and Mac. If you live in Apple's ecosystem and work alone or on a small team, Coworker.ai handles personal AI tasks without forcing you to manage multiple accounts. Just know its limit. The app serves the individual, with no shared memory for a team to build on.

Best For: Sentra

Choose Sentra when more than one person or agent has to act on the same facts and trust them. Sentra holds decisions, commitments, and evolving facts in one graph that humans and agents read and write together. What one agent learns, every agent knows, so context stops fragmenting across sessions, tools, and people.

The clearest fit is an engineering, sales, or ops org deploying AI agents that need shared, durable memory. A coding agent in Cursor, a support agent in Zendesk, and a rep working a deal in HubSpot all draw from the same source of truth instead of isolated per-session context. Sentra also suits teams that need commitments tracked and stale facts invalidated automatically, where a verbal promise or a deprecated price restated as current carries real cost. It connects through REST and MCP to the tools and models you already run.

Verdict

If you want a personal assistant that puts ChatGPT, Claude, and Gemini behind one interface on your iPhone, iPad, or Mac, Coworker.ai is the simpler, faster path. You download it, start the 30-day trial, and draft, translate, or generate images without juggling three separate accounts. For a writer, student, or solo founder working on Apple devices, that breadth of model access in one app is the whole win.

If your organization needs humans and AI agents to share one source of truth, Sentra is the only product here built for that problem. Coworker.ai stores no shared org memory. Each session belongs to one person, so what one user learns never reaches a teammate or another agent. Sentra writes every decision, fact, and commitment into a single bi-temporal graph that every human and agent reads and writes through REST or MCP. That graph tracks verbal commitments from the moment they are spoken, flags contradictions, and invalidates stale facts with a second timestamp so agents never restate yesterday as today.

These products answer different questions. Pick Coworker.ai for individual productivity. Pick Sentra when your agents and your people need to remember the same things.

FAQs

Can Coworker.ai be used by teams?

Coworker.ai is built as a single-user app, and its App Store listing describes individual productivity rather than team workflows. Each session belongs to one person, with no shared knowledge base, multi-user collaboration, or team-wide memory. Small teams can each buy a subscription, but they will not share context across people.

Does Sentra replace my existing AI models or agents?

No. Sentra is the memory layer underneath your stack, and it connects to Claude, ChatGPT, Cursor, Codex, and 200+ other tools through REST or MCP. Your agents keep doing their work, and they read and write to one shared graph so what you teach one agent, every agent remembers.

What does "bi-temporal" mean in practice?

Every fact in Sentra carries two timestamps, one for when it became true and one for when it stopped being true. When a fact changes, Sentra invalidates the old version instead of deleting it, so the history stays intact. Your agents never restate a deprecated price or stale policy as if it were still current.

Does Sentra work on mobile?

Sentra is an org-wide memory layer rather than a consumer app, so you access it through your existing tools and agents rather than a standalone mobile interface. Coworker.ai is the mobile-first option here, running on iOS, iPadOS, macOS, and visionOS with cross-device sync. The two products serve different surfaces.

Is Coworker.ai the same as coworker.com or coworker.org?

No. Coworker.ai is the AI assistant app from Coworker LLC, and it is the only product compared here. The name coworker.com belongs to an unrelated coworking-space marketplace, and coworker.org is a separate labor-advocacy nonprofit.